How to better manage work, machinery, inputs, crop and livestock condition, product traceability and cost price
Crop production, livestock, forestry, fisheries and other primary production areas differ in processes, machinery used, biological cycles and principal risks. Therefore, a separate analysis with more specific solutions and priorities is being prepared for each business area.
In livestock, every biological signal has a time value: an early detected disease, oestrus, feed or environmental problem can directly reduce losses. Digitalisation creates value only when the alert becomes a clear human task and a measured result.
Crop production economics depends on decisions made for a specific field, zone and narrow operating window. Digitalisation creates value when the plan, actual machinery performance, biological condition, yield and costs form one cycle.
In forestry, decisions operate over decades, whilst violations and market changes can alter value within days. Digitalisation must connect long-term forest modelling with operational management of works, risks and timber origin.
The value of procurement and cooperation arises from scale: many farms must operate as one reliable portfolio of supply, quality, logistics and sales. Digitalisation must create transparency for the member and speed of decision-making for the cooperative.
In fisheries and aquaculture, biological conditions can change rapidly, and collecting reliable measurements is complex. Digitalisation must connect environmental signals, production groups, worker actions and sales outcomes.
Agricultural service companies compete not only on machinery or specialists, but on the ability to perform work at the right time and reliably prove the result. Digitalisation must connect client need, capacity planning, machinery fact and margin.
The farm manager has to collect information manually, data is duplicated, and decisions are based on an incomplete or delayed picture.
The greatest value arises when data on fields, livestock, operations, machinery, materials and produce are not stored separately, but form a single production history. This enables visibility not only of what was planned, but also what was actually carried out, how much it cost and what result it delivered.
Select a single crop, group of fields, herd or produce flow and connect plan, tasks, materials, machinery, result and cost.
Agriculture and primary production have high digitalisation potential, but the greatest value does not lie in individual smart technologies. It emerges when the farm reliably connects daily operations, machinery and material usage, biological results and finances.
The full digital sector analysis is presented below. A more detailed analysis tailored to the specific operating model is available on the business area pages.
The sector encompasses crop production, livestock farming, horticulture and market gardening, mixed farms, forestry, fisheries, aquaculture and other primary production. Whilst the machinery used and production processes differ, all these business areas share the need to manage limited resources, biological cycles, seasonal work, traceability and changing natural conditions precisely.
Sowing, harvesting, reproduction, feeding, treatment or other work cannot be freely rescheduled – delayed action can directly reduce the outcome.
Precipitation, temperature, soil, water availability, diseases, pests and extreme events can alter the outcome of even a well-planned season.
Tractors, combine harvesters, farm, milking, feeding, storage or irrigation equipment must be reliably used when it is needed most.
Information is created by machinery, sensors, satellites, laboratories, veterinary specialists, workers, accounting, buyers and public systems.
Large farms can use advanced integrated systems, whilst smaller ones still rely on manufacturers' apps, spreadsheets and paper journals.
Reliable history of production origin, quality, certification and sustainability helps meet buyer requirements and justify greater production value.
In the strategic plans of the European Union's Common Agricultural Policy, digitalisation is identified as one of the directions for modernising the sector. From 12 September 2025, the EU Data Act strengthens the ability of users of connected technology and equipment to access data generated during their use. At the same time, a common European agricultural data space is being developed, and Copernicus satellite data are increasingly used for monitoring crop and land conditions.
Work, materials, crop or livestock conditions and documents are recorded on paper, in messages or only at the end of the season.
Accounting, equipment manufacturers' portals or separate field and herd programmes are used, but data are not interconnected.
A farm management system, telematics, sensors or precision farming tools are in operation, but the plan, actual performance, costs and documents are still visible separately.
Fields, livestock, equipment, work, materials, warehouse and production are managed using common identifiers and clear statuses.
Work, material rates, risks, equipment capacity and profitability are managed based on actual and forecast data.
Robotics, AI and optimisation systems perform part of clearly defined operations, and recommendations are continuously evaluated according to biological and financial results.
Many farms already have plenty of technology. Machinery, sensors, accounting systems, laboratories and public platforms accumulate vast amounts of data, yet these often remain in separate systems. As a result, the farm manager still lacks a straightforward answer as to what was done in a specific field or livestock group, what it cost and what result it delivered.
The primary task of digitalisation is to connect plan with actual. Work tasks must be linked to a specific field or livestock group, machinery, worker, materials consumed and output produced. Only then do satellite data, machinery telematics or advanced forecasts begin to support decision-making, rather than merely generating yet another report.
It is worth starting with one clear production cycle – a single crop season, a specific herd or production flow – and measuring the change in costs, labour and results.
Field, crop, herd, machinery, laboratory test, warehouse, sales and accounting data are stored in different programmes, manufacturers' portals, spreadsheets or paper journals.
Plans for sowing, fertilising, spraying, feeding, treatment, care and harvesting are communicated verbally, via messages or in separate programmes, whilst completed work is often recorded only later.
Satellite, meteorological, soil, sensor, imagery and productivity data are not linked to specialist inspections and a clear action sequence.
Working time, equipment, fuel, materials, feed, veterinary care, losses and production volume are not consistently assigned to a specific field, crop, herd or batch.
Tractors, harvesters, automated steering, milking, feeding and other equipment collect data on different platforms and in different formats.
The purchase, issue, batch and consumption of seeds, fertilisers, crop protection products, feed and other materials are recorded at different times or in different places.
The history of a field or livestock group, materials used, work performed, production batch, storage, quality testing and sale are not linked by common identifiers.
Information about fields, fertilisation, crop protection, livestock, traceability, environmental protection and support is collected for separate systems and documents.
The tasks, locations, materials, working time and quality of performance for employees, contractors and equipment are communicated through several informal channels.
The greatest value arises when data on fields, livestock, operations, machinery, materials and produce are not stored separately, but form a single production history. This enables visibility not only of what was planned, but also what was actually carried out, how much it cost and what result it delivered.
The most important farm data is scattered across different systems
Single production cycle management system
For a single crop, field group, herd or product flow, it links the plan, tasks, actual work, materials, results and cost.
Farm plans are insufficiently linked to what has actually been performed
It is difficult to know precisely whether work was completed on time and according to plan, how many materials were consumed, who is responsible for deviation and how it affected the outcome.
Single production cycle management system
For a single crop, field group, herd or product flow, it links the plan, tasks, actual work, materials, results and cost.
The true cost per field, crop or livestock group is unclear
Single production cycle management system
For a single crop, field group, herd or product flow, it links the plan, tasks, actual work, materials, results and cost.
Seasonal work is coordinated by phone calls and messages
During critical periods it is easy to be late, duplicate work, use the wrong material or lose information about what was performed and when.
Single production cycle management system
For a single crop, field group, herd or product flow, it links the plan, tasks, actual work, materials, results and cost.
Farm plans are insufficiently linked to what has actually been performed
It is difficult to know precisely whether work was completed on time and according to plan, how many materials were consumed, who is responsible for deviation and how it affected the outcome.
Mobile work and materials management application
Provides employees and contractors with the task, object, equipment, materials and deadline, and allows completion and deviations to be recorded on site.
Material balances and actual consumption are not always accurate
Mobile work and materials management application
Provides employees and contractors with the task, object, equipment, materials and deadline, and allows completion and deviations to be recorded on site.
There is no need to change all systems in use immediately. Most often the best approach is to select one core farm management platform, connect it to the most important equipment and accounting data sources, and leave employees with a simple daily workflow.
For a single crop, field group, herd or product flow, it links the plan, tasks, actual work, materials, results and cost.
Provides employees and contractors with the task, object, equipment, materials and deadline, and allows completion and deviations to be recorded on site.
Connects work, location, fuel, energy, condition, downtime and operation data from the most important machinery units, farm equipment and sensors.
Connects satellite, meteorological, laboratory, sensor, image and productivity data with specialist inspections and specific actions.
Links the production site, materials used, work performed, production batch, quality data, reports, sales and financial result.
A field, animal, equipment unit, material and production batch may have different codes, but it must be clear that they refer to the same object.
The worker must have a clear task, confirmation of completion, materials used and reason for deviation, whilst available equipment data is collected automatically.
Movement or an activated unit alone does not prove proper completion. A link to the field, livestock group, work, material, worker and result is required.
The system must show what needs to be checked, who will do it and by when. Otherwise, alerts quickly become ignored noise.
It must be clear who can use the data and how to export it, whilst return on investment is evaluated through a season, production cycle or control groups.
Select one crop, field group, herd or production stream and identify where the plan, actual work, materials and results diverge.
Agree which data and integrations are necessary for one measurable scenario, without attempting to cover the entire farm immediately.
Connect the plan, worker actions, machinery, materials consumed, deviations and production result achieved.
Verify that data is recorded on time, employees are using the solution, and the selected cost, time or productivity KPIs are improving.
Expand the proven model to other production sites, link it to financial results and only then implement more advanced automation.
Shows whether actual data appear in the system whilst they can still be used for decisions.
Helps assess whether work is performed during the optimal period and whether machinery and labour capacity are sufficient.
Shows the accuracy of accounting for seeds, fertilisers, feed, crop protection products and other inputs.
Helps compare resource efficiency across different fields, crops, herds or technologies.
Shows whether machinery maintenance and preparation for critical work are managed proactively.
Helps assess whether monitoring of crops, livestock and equipment enables sufficiently early response.
Shows actual production result and allows comparison across seasons and production methods.
Shows which crops, fields, livestock groups or technologies actually generate profit.
Advanced technologies are not a good first step if the farm does not yet have reliable data on operations, materials, machinery and results. AI, robotics or forecasts must address a clear problem, and their benefit should be assessed according to actual change in yield, productivity, costs or labour time.
The system selects different seeding, fertilisation, spraying, irrigation, feeding or other material rates according to field zone, plant condition or livestock group requirement.
AI models can compare satellite, drone, meteorological, soil and previous season data and identify plots that agronomists should inspect first.
Wearable sensors, video analysis, milking, feeding and environmental data help detect changes in animal activity, health, reproduction or productivity.
Autonomous vehicles, robots and computer vision can perform weeding, spraying, sowing, crop monitoring or other clearly defined tasks.
Standardised interfaces, clear access rights and consent management allow the farm to choose which equipment or production data to transfer to consultants, suppliers, buyers or institutions.
A review will be conducted of how work is currently planned and recorded, where machinery, materials, crop or livestock data is stored, and what prevents true cost accounting visibility. The first stage will then be defined, with measurable benefits.
